{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os,sys,inspect\n",
    "currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))\n",
    "parentdir = os.path.dirname(currentdir)\n",
    "sys.path.insert(0,parentdir) \n",
    "\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from browser import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "TUNABLE = ['m_groups', 'k_winners', 'eps', 'fpartition', 'forget_mu', 'boost_strength', 'boost_strength_factor']\n",
    "NUMERIC_TUNABLE = ['m_groups', 'k_winners', 'eps', 'forget_mu', 'boost_strength', 'boost_strength_factor']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 96 experiments\n"
     ]
    }
   ],
   "source": [
    "exps = [\n",
    "    'Flat_PTB_Explore',\n",
    "    'Flat_PTB_Snipe',\n",
    "    'Flat_PTB_Snipe2',\n",
    "]\n",
    "\n",
    "paths = [os.path.expanduser(\"~/s3_jgordon/ray/results/{}\".format(e)) for e in exps]\n",
    "df = load_many(paths)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[~df.k_winners_pct.isnull(), 'k_winners'] = df.k_winners_pct * df.m_groups\n",
    "df.k_winners = df.k_winners.astype(int)\n",
    "\n",
    "for tp in TUNABLE:\n",
    "    if tp not in df:\n",
    "        df[tp] = None\n",
    "        \n",
    "df.fillna(value={\n",
    "    'forget_mu': 0.0,\n",
    "    'dropout_p': 0.0,\n",
    "    'balance_part_winners': False\n",
    "}, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatter_all_tunable(df, params=NUMERIC_TUNABLE, ppl_cutoff=220):\n",
    "    fig, axs = plt.subplots(len(params), 1, figsize=(8, 14), \n",
    "                            dpi=144, \n",
    "                            gridspec_kw={'hspace': 0.7})\n",
    "    for ax, p in zip(axs, params):\n",
    "        df[df.val_pred_ppl_min <= ppl_cutoff].plot(kind='scatter', x=p, y='val_pred_ppl_min', c='train_pred_ppl_min', colormap='viridis', ax=ax)\n",
    "        ax.set_title(\"%s vs min val PPL\" % p)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x2016 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_all_tunable(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Without Embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>m_groups</th>\n",
       "      <th>k_winners</th>\n",
       "      <th>eps</th>\n",
       "      <th>fpartition</th>\n",
       "      <th>forget_mu</th>\n",
       "      <th>boost_strength</th>\n",
       "      <th>boost_strength_factor</th>\n",
       "      <th>weight_sparsity</th>\n",
       "      <th>x_b_norm</th>\n",
       "      <th>balance_part_winners</th>\n",
       "      <th>mult_integration</th>\n",
       "      <th>embedding_kind</th>\n",
       "      <th>val_pred_ppl_min</th>\n",
       "      <th>val_pred_acc_max</th>\n",
       "      <th>train_pred_ppl_min</th>\n",
       "      <th>epoch_val_pred_ppl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>4000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.025000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.97</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>149.533360</td>\n",
       "      <td>23.207171</td>\n",
       "      <td>65.229777</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>4000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>155.133020</td>\n",
       "      <td>22.570667</td>\n",
       "      <td>84.297827</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>4000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.025000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.97</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>157.728945</td>\n",
       "      <td>22.343958</td>\n",
       "      <td>57.851861</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>4000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.709427</td>\n",
       "      <td>22.469333</td>\n",
       "      <td>84.384822</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>5000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.872428</td>\n",
       "      <td>22.691899</td>\n",
       "      <td>68.133196</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>7000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>162.030516</td>\n",
       "      <td>22.363878</td>\n",
       "      <td>45.408591</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>7000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>162.083793</td>\n",
       "      <td>22.406375</td>\n",
       "      <td>86.599488</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>3000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.035000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.97</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>164.965017</td>\n",
       "      <td>22.027888</td>\n",
       "      <td>110.877298</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.035000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.97</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>165.441337</td>\n",
       "      <td>22.013280</td>\n",
       "      <td>89.712456</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>8000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.384175</td>\n",
       "      <td>21.865870</td>\n",
       "      <td>50.688927</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>3000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.035000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.97</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.891307</td>\n",
       "      <td>22.479416</td>\n",
       "      <td>63.550150</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>7000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>171.233200</td>\n",
       "      <td>21.512616</td>\n",
       "      <td>88.577685</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>4000</td>\n",
       "      <td>20</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>172.745524</td>\n",
       "      <td>22.017333</td>\n",
       "      <td>87.597685</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>7000</td>\n",
       "      <td>20</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>173.047570</td>\n",
       "      <td>21.809326</td>\n",
       "      <td>57.430864</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>7000</td>\n",
       "      <td>24</td>\n",
       "      <td>0.593219</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.016094</td>\n",
       "      <td>0.754832</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>173.582597</td>\n",
       "      <td>21.734666</td>\n",
       "      <td>59.114142</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>7000</td>\n",
       "      <td>20</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175.468927</td>\n",
       "      <td>21.870941</td>\n",
       "      <td>57.844657</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>7000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175.497827</td>\n",
       "      <td>21.528552</td>\n",
       "      <td>68.451441</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>4000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175.782292</td>\n",
       "      <td>21.996296</td>\n",
       "      <td>78.870546</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>7000</td>\n",
       "      <td>30</td>\n",
       "      <td>0.669489</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.018861</td>\n",
       "      <td>1.169682</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>177.845409</td>\n",
       "      <td>21.659173</td>\n",
       "      <td>61.190414</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>7000</td>\n",
       "      <td>7</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178.192506</td>\n",
       "      <td>20.714475</td>\n",
       "      <td>112.657826</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5221</td>\n",
       "      <td>22</td>\n",
       "      <td>0.487196</td>\n",
       "      <td>0.452876</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.475382</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>179.147110</td>\n",
       "      <td>21.379961</td>\n",
       "      <td>55.514601</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.035000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>180.802274</td>\n",
       "      <td>20.818061</td>\n",
       "      <td>109.780877</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>7000</td>\n",
       "      <td>7</td>\n",
       "      <td>0.588474</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.022133</td>\n",
       "      <td>1.014024</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.118973</td>\n",
       "      <td>20.636692</td>\n",
       "      <td>98.470202</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>7000</td>\n",
       "      <td>8</td>\n",
       "      <td>0.634966</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.019176</td>\n",
       "      <td>0.844524</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181.916666</td>\n",
       "      <td>20.655010</td>\n",
       "      <td>94.701623</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>4000</td>\n",
       "      <td>80</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>184.283028</td>\n",
       "      <td>21.446215</td>\n",
       "      <td>85.464933</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>4000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>184.735396</td>\n",
       "      <td>21.672840</td>\n",
       "      <td>88.586975</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>7000</td>\n",
       "      <td>30</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.005000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>186.189591</td>\n",
       "      <td>21.035803</td>\n",
       "      <td>54.449358</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>4000</td>\n",
       "      <td>80</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>188.182702</td>\n",
       "      <td>20.460823</td>\n",
       "      <td>155.715283</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>7000</td>\n",
       "      <td>34</td>\n",
       "      <td>0.796611</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.022308</td>\n",
       "      <td>0.813055</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>188.414072</td>\n",
       "      <td>20.977241</td>\n",
       "      <td>55.959882</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5000</td>\n",
       "      <td>40</td>\n",
       "      <td>0.450389</td>\n",
       "      <td>0.119279</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.861009</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>188.646976</td>\n",
       "      <td>20.774355</td>\n",
       "      <td>99.860362</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244.667202</td>\n",
       "      <td>17.392593</td>\n",
       "      <td>198.199052</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>7000</td>\n",
       "      <td>13</td>\n",
       "      <td>0.458370</td>\n",
       "      <td>0.437357</td>\n",
       "      <td>0.007977</td>\n",
       "      <td>0.766594</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>252.210784</td>\n",
       "      <td>17.983902</td>\n",
       "      <td>180.376648</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>8000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>252.771757</td>\n",
       "      <td>16.804781</td>\n",
       "      <td>219.026779</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>8000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>263.288485</td>\n",
       "      <td>16.568393</td>\n",
       "      <td>244.956938</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5000</td>\n",
       "      <td>439</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.476656</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.116153</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>264.066107</td>\n",
       "      <td>18.587843</td>\n",
       "      <td>174.432677</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>4000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>None</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>267.040836</td>\n",
       "      <td>17.700000</td>\n",
       "      <td>199.254060</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5466</td>\n",
       "      <td>271</td>\n",
       "      <td>0.363649</td>\n",
       "      <td>0.389563</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.522465</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277.124967</td>\n",
       "      <td>15.998612</td>\n",
       "      <td>257.620266</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>7000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.402180</td>\n",
       "      <td>0.397973</td>\n",
       "      <td>0.009692</td>\n",
       "      <td>1.125165</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>281.013971</td>\n",
       "      <td>16.723009</td>\n",
       "      <td>205.949667</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>4000</td>\n",
       "      <td>40</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>282.159515</td>\n",
       "      <td>18.082716</td>\n",
       "      <td>248.627352</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>7000</td>\n",
       "      <td>26</td>\n",
       "      <td>0.643324</td>\n",
       "      <td>0.328484</td>\n",
       "      <td>0.005265</td>\n",
       "      <td>0.948042</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>282.259688</td>\n",
       "      <td>16.156814</td>\n",
       "      <td>211.187379</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>7000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.672613</td>\n",
       "      <td>0.301799</td>\n",
       "      <td>0.006074</td>\n",
       "      <td>0.685615</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>286.045803</td>\n",
       "      <td>15.492090</td>\n",
       "      <td>233.932968</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7000</td>\n",
       "      <td>26</td>\n",
       "      <td>0.594523</td>\n",
       "      <td>0.364394</td>\n",
       "      <td>0.009932</td>\n",
       "      <td>0.678338</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>287.956944</td>\n",
       "      <td>15.714405</td>\n",
       "      <td>241.470804</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5190</td>\n",
       "      <td>164</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.17483</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.105501</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>288.382356</td>\n",
       "      <td>17.359700</td>\n",
       "      <td>328.284816</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7000</td>\n",
       "      <td>6</td>\n",
       "      <td>0.483391</td>\n",
       "      <td>0.310452</td>\n",
       "      <td>0.006410</td>\n",
       "      <td>0.936584</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>299.312030</td>\n",
       "      <td>15.799611</td>\n",
       "      <td>236.572892</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>7000</td>\n",
       "      <td>21</td>\n",
       "      <td>0.452550</td>\n",
       "      <td>0.30867</td>\n",
       "      <td>0.009381</td>\n",
       "      <td>0.766783</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>313.493275</td>\n",
       "      <td>15.946711</td>\n",
       "      <td>243.237225</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5453</td>\n",
       "      <td>15</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.211701</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.067430</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>322.009379</td>\n",
       "      <td>16.187344</td>\n",
       "      <td>257.327728</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>4000</td>\n",
       "      <td>150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>322.287556</td>\n",
       "      <td>16.612346</td>\n",
       "      <td>305.678443</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7000</td>\n",
       "      <td>23</td>\n",
       "      <td>0.691022</td>\n",
       "      <td>0.434081</td>\n",
       "      <td>0.006510</td>\n",
       "      <td>1.033591</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>323.921014</td>\n",
       "      <td>14.665279</td>\n",
       "      <td>281.367261</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>343.306769</td>\n",
       "      <td>16.451852</td>\n",
       "      <td>345.009104</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5000</td>\n",
       "      <td>899</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.491606</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.552303</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>356.124656</td>\n",
       "      <td>14.759367</td>\n",
       "      <td>234.401898</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5910</td>\n",
       "      <td>190</td>\n",
       "      <td>0.548464</td>\n",
       "      <td>0.266009</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.261804</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>360.805184</td>\n",
       "      <td>12.948931</td>\n",
       "      <td>526.293090</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5000</td>\n",
       "      <td>921</td>\n",
       "      <td>0.472143</td>\n",
       "      <td>0.0910026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.502225</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>361.819155</td>\n",
       "      <td>13.656120</td>\n",
       "      <td>260.168279</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>4000</td>\n",
       "      <td>150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>416.070079</td>\n",
       "      <td>13.750617</td>\n",
       "      <td>454.064077</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>455.708744</td>\n",
       "      <td>12.832099</td>\n",
       "      <td>591.038453</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>4000</td>\n",
       "      <td>15</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>458.519413</td>\n",
       "      <td>12.670370</td>\n",
       "      <td>542.036964</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>4000</td>\n",
       "      <td>80</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>478.466163</td>\n",
       "      <td>12.965432</td>\n",
       "      <td>603.494092</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>507.003820</td>\n",
       "      <td>12.579012</td>\n",
       "      <td>596.373978</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2000</td>\n",
       "      <td>6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>509.343218</td>\n",
       "      <td>10.407407</td>\n",
       "      <td>560.517984</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>527.973285</td>\n",
       "      <td>12.235802</td>\n",
       "      <td>649.732477</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5000</td>\n",
       "      <td>249</td>\n",
       "      <td>0.840724</td>\n",
       "      <td>0.0998685</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.561221</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>581.734947</td>\n",
       "      <td>8.320289</td>\n",
       "      <td>309.324191</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>83 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    m_groups  k_winners       eps fpartition  forget_mu  boost_strength  \\\n",
       "86      4000         15  0.500000        0.9      0.025        1.000000   \n",
       "90      4000         15  0.500000        0.9      0.020        1.000000   \n",
       "49      4000         15  0.500000        0.8      0.025        1.000000   \n",
       "57      4000         15  0.500000        0.9      0.020        1.000000   \n",
       "48      5000         15  0.500000       0.85      0.010        1.000000   \n",
       "..       ...        ...       ...        ...        ...             ...   \n",
       "59      4000         80  0.500000        0.4      0.020        1.000000   \n",
       "61      5000         50  0.500000       0.35      0.020        1.000000   \n",
       "70      2000          6  0.000000       0.25      0.020        1.000000   \n",
       "62      5000         50  0.500000       0.35      0.020        1.000000   \n",
       "0       5000        249  0.840724  0.0998685      0.000        0.561221   \n",
       "\n",
       "    boost_strength_factor weight_sparsity  x_b_norm  balance_part_winners  \\\n",
       "86                   0.97            None      True                 False   \n",
       "90                   0.80            None      True                  True   \n",
       "49                   0.97            None      True                 False   \n",
       "57                   1.00            None      True                  True   \n",
       "48                   1.00             0.3      True                 False   \n",
       "..                    ...             ...       ...                   ...   \n",
       "59                   0.80            None     False                  True   \n",
       "61                   1.00            None     False                  True   \n",
       "70                   1.00            None      True                  True   \n",
       "62                   1.00            None     False                  True   \n",
       "0                    1.00             NaN     False                 False   \n",
       "\n",
       "    mult_integration embedding_kind  val_pred_ppl_min  val_pred_acc_max  \\\n",
       "86              True            NaN        149.533360         23.207171   \n",
       "90              True            NaN        155.133020         22.570667   \n",
       "49              True            NaN        157.728945         22.343958   \n",
       "57              True            NaN        160.709427         22.469333   \n",
       "48              True            NaN        160.872428         22.691899   \n",
       "..               ...            ...               ...               ...   \n",
       "59              True            NaN        478.466163         12.965432   \n",
       "61              True            NaN        507.003820         12.579012   \n",
       "70              True            NaN        509.343218         10.407407   \n",
       "62              True            NaN        527.973285         12.235802   \n",
       "0               True            NaN        581.734947          8.320289   \n",
       "\n",
       "    train_pred_ppl_min  epoch_val_pred_ppl  \n",
       "86           65.229777                  50  \n",
       "90           84.297827                  47  \n",
       "49           57.851861                  45  \n",
       "57           84.384822                  45  \n",
       "48           68.133196                  55  \n",
       "..                 ...                 ...  \n",
       "59          603.494092                   0  \n",
       "61          596.373978                   0  \n",
       "70          560.517984                   2  \n",
       "62          649.732477                   0  \n",
       "0           309.324191                   0  \n",
       "\n",
       "[83 rows x 16 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.embedding_kind.isnull()].sort_values('val_pred_ppl_min')[TUNABLE + ['weight_sparsity', 'x_b_norm', 'balance_part_winners', 'mult_integration', 'embedding_kind'] + \n",
    "                                   ['val_pred_ppl_min', 'val_pred_acc_max', 'train_pred_ppl_min', 'epoch_val_pred_ppl']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>m_groups</th>\n",
       "      <th>k_winners</th>\n",
       "      <th>eps</th>\n",
       "      <th>fpartition</th>\n",
       "      <th>forget_mu</th>\n",
       "      <th>boost_strength</th>\n",
       "      <th>boost_strength_factor</th>\n",
       "      <th>weight_sparsity</th>\n",
       "      <th>x_b_norm</th>\n",
       "      <th>balance_part_winners</th>\n",
       "      <th>mult_integration</th>\n",
       "      <th>embedding_kind</th>\n",
       "      <th>val_pred_ppl_min</th>\n",
       "      <th>val_pred_acc_max</th>\n",
       "      <th>train_pred_ppl_min</th>\n",
       "      <th>epoch_val_pred_ppl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1000</td>\n",
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       "      <td>0.00</td>\n",
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       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>134.686125</td>\n",
       "      <td>23.059259</td>\n",
       "      <td>65.109254</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.50</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>177.360827</td>\n",
       "      <td>20.409877</td>\n",
       "      <td>123.929287</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.50</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>178.504244</td>\n",
       "      <td>20.375309</td>\n",
       "      <td>111.730235</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>4000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>glove</td>\n",
       "      <td>180.837370</td>\n",
       "      <td>21.213580</td>\n",
       "      <td>128.259115</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>glove</td>\n",
       "      <td>191.500516</td>\n",
       "      <td>21.032099</td>\n",
       "      <td>141.036298</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>glove</td>\n",
       "      <td>248.209167</td>\n",
       "      <td>18.882716</td>\n",
       "      <td>250.072538</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.50</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>285.422338</td>\n",
       "      <td>18.162963</td>\n",
       "      <td>296.663770</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.85</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>glove</td>\n",
       "      <td>288.996243</td>\n",
       "      <td>14.880247</td>\n",
       "      <td>273.512578</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>glove</td>\n",
       "      <td>291.829646</td>\n",
       "      <td>18.622222</td>\n",
       "      <td>323.001734</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>5000</td>\n",
       "      <td>50</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>glove</td>\n",
       "      <td>434.616214</td>\n",
       "      <td>13.854321</td>\n",
       "      <td>547.006341</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.50</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>938.758771</td>\n",
       "      <td>10.223457</td>\n",
       "      <td>1161.010146</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.85</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>961.044750</td>\n",
       "      <td>7.590123</td>\n",
       "      <td>1264.578652</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>4000</td>\n",
       "      <td>100</td>\n",
       "      <td>0.50</td>\n",
       "      <td>None</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>ptb_fasttext</td>\n",
       "      <td>985.821118</td>\n",
       "      <td>9.286420</td>\n",
       "      <td>1054.394551</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    m_groups  k_winners   eps fpartition  forget_mu  boost_strength  \\\n",
       "36      1000         25  0.00       None       0.02             1.0   \n",
       "81      4000        100  0.50       None       0.02             1.0   \n",
       "84      4000        100  0.50       None       0.02             1.0   \n",
       "75      4000         50  0.00       0.35       0.02             1.0   \n",
       "78      4000        100  0.00       0.35       0.02             1.0   \n",
       "94      5000         50  0.50       0.35       0.02             1.0   \n",
       "82      4000        100  0.50       None       0.02             1.0   \n",
       "76      4000        100  0.85       None       0.02             1.0   \n",
       "77      4000        100  0.00       0.35       0.02             1.0   \n",
       "93      5000         50  0.50       0.35       0.02             1.0   \n",
       "80      4000        100  0.50       None       0.02             1.0   \n",
       "79      4000        100  0.85       None       0.02             1.0   \n",
       "83      4000        100  0.50       None       0.02             1.0   \n",
       "\n",
       "    boost_strength_factor weight_sparsity  x_b_norm  balance_part_winners  \\\n",
       "36                    0.8            None      True                 False   \n",
       "81                    0.8            None     False                 False   \n",
       "84                    0.8            None     False                 False   \n",
       "75                    0.8            None     False                 False   \n",
       "78                    0.9            None     False                 False   \n",
       "94                    1.0            None     False                  True   \n",
       "82                    0.8            None     False                 False   \n",
       "76                    0.8            None     False                 False   \n",
       "77                    0.9            None     False                 False   \n",
       "93                    1.0            None     False                  True   \n",
       "80                    0.8            None     False                 False   \n",
       "79                    0.8            None     False                 False   \n",
       "83                    0.8            None     False                 False   \n",
       "\n",
       "    mult_integration embedding_kind  val_pred_ppl_min  val_pred_acc_max  \\\n",
       "36             False   ptb_fasttext        134.686125         23.059259   \n",
       "81             False   ptb_fasttext        177.360827         20.409877   \n",
       "84             False   ptb_fasttext        178.504244         20.375309   \n",
       "75              True          glove        180.837370         21.213580   \n",
       "78             False          glove        191.500516         21.032099   \n",
       "94              True          glove        248.209167         18.882716   \n",
       "82             False   ptb_fasttext        285.422338         18.162963   \n",
       "76             False          glove        288.996243         14.880247   \n",
       "77             False          glove        291.829646         18.622222   \n",
       "93              True          glove        434.616214         13.854321   \n",
       "80             False   ptb_fasttext        938.758771         10.223457   \n",
       "79             False   ptb_fasttext        961.044750          7.590123   \n",
       "83             False   ptb_fasttext        985.821118          9.286420   \n",
       "\n",
       "    train_pred_ppl_min  epoch_val_pred_ppl  \n",
       "36           65.109254                  23  \n",
       "81          123.929287                  32  \n",
       "84          111.730235                  47  \n",
       "75          128.259115                  70  \n",
       "78          141.036298                  30  \n",
       "94          250.072538                   9  \n",
       "82          296.663770                   2  \n",
       "76          273.512578                  23  \n",
       "77          323.001734                   3  \n",
       "93          547.006341                   0  \n",
       "80         1161.010146                   0  \n",
       "79         1264.578652                   0  \n",
       "83         1054.394551                   0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[~df.embedding_kind.isnull()].sort_values('val_pred_ppl_min')[TUNABLE + ['weight_sparsity', 'x_b_norm', 'balance_part_winners', 'mult_integration', 'embedding_kind'] + \n",
    "                                   ['val_pred_ppl_min', 'val_pred_acc_max', 'train_pred_ppl_min', 'epoch_val_pred_ppl']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 2, dpi=144, figsize=(10, 5), gridspec_kw={'wspace': 0.5})\n",
    "df[df.val_pred_ppl_min < 200].plot(kind='scatter', x='k_winners', y='fpartition', c='val_pred_ppl_min', colormap='viridis', ax=axs[0])\n",
    "df[df.val_pred_ppl_min < 200].plot(kind='scatter', x='k_winners', y='m_groups', c='val_pred_ppl_min', colormap='viridis', ax=axs[1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Normalization slows down time-to-peak')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['norm_int'] = 0\n",
    "df.loc[df.x_b_norm, 'norm_int'] = 1\n",
    "df.plot(kind='scatter', x='norm_int', y='epoch_val_pred_ppl')\n",
    "plt.title(\"Normalization slows down time-to-peak\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
